Hung-Cheng Chen

Generative AI (GenAI) challenges traditional technology integration frameworks by introducing agentic systems that actively participate in meaning-making, requiring educators to shift from tool operation to cognitive orchestration. This study introduces the MTA–TPACK Dynamic Collaboration Spiral, a theoretical framework that integrates Meta-Task Awareness (MTA) to explain how static knowledge resources are dynamically activated during human–AI collaboration. We empirically illustrate this framework through a two-phase scientific visualization task concerning typhoon–terrain interactions, utilizing Midjourney for human-led orchestration and GPT-4o for closed-loop refinement. The results demonstrate that successful integration requires translating abstract disciplinary knowledge into precise, AI-intelligible visual constraints rather than relying solely on technical prompting skills. Furthermore, we document how evaluation practices evolve from simple error correction to structured, AI-assisted diagnosis. The resulting visual artifacts embody Visible Pedagogical Thinking (VPT)—externalized cognitive constructs that make expert reasoning inspectable and reusable. By foregrounding evaluation-centered task design, this study provides a transferable, theoretically grounded account of how human–AI collaboration can remain pedagogically meaningful. The model contributes to sustainable pedagogical innovation by offering a roadmap for strengthening teachers’ long-term epistemic agency in AI-mediated design environments.

Generative AI challenges traditional technology integration frameworks by introducing agentic systems that actively participate in meaning-making and representation. Existing TPACK-based extensions have identified new knowledge domains required for AI integration, yet they offer insufficient explanations of how such knowledge is dynamically activated during human–AI collaboration. This study proposes the MTA–TPACK Dynamic Collaboration Spiral, a theoretical framework that integrates Meta-Task Awareness (MTA) with TPACK to explain how static knowledge resources are transformed into visible pedagogical reasoning through iterative human–AI interaction. Within this framework, MTA functions as a dynamic navigation engine that guides experts along a Generate–Evaluate–Refine trajectory, enabling principled orchestration of AI participation while maintaining epistemic responsibility. The framework is illustrated through a two-phase scientific visualization task on typhoon–terrain interactions, using Midjourney and GPT-4o. The results show how disciplinary knowledge must be reformulated as AI-interpretable constraints and how evaluation practices evolve when AI systems participate in closed-loop feedback. The resulting visual artifacts embody what is termed Visible Pedagogical Thinking—externalized cognitive constructs that make expert reasoning inspectable. By foregrounding evaluation-centered task design, this study provides a transferable account of how human–AI collaboration can remain pedagogically meaningful by rendering expert reasoning observable and reusable across iterative generative workflows. In doing so, the model contributes to sustainable pedagogical innovation by strengthening teachers’ long-term epistemic agency in AI-mediated design environments.

This study investigates the mechanisms of topographic steering and the resultant track morphology of typhoon-like vortices over complex terrain. Leveraging a dynamic model based on potential vorticity (PV) conservation, we conducted a comprehensive sensitivity analysis over both an idealized bell-shaped mountain and the realistic topography of Taiwan. Results indicate that a triad of controls governs track evolution: vortex intensity (α), terrain geometry (dhB*/dt*), and interaction time (impinging angle γ). To quantify predictability, we introduce the Track Divergence Percentage (td), which partitions the phase space into distinct Track Diverging (TDZ) and Converging (TCZ) Zones. While idealized simulations established this fundamental structure, realistic experiments incorporating vortex decay revealed that orographic complexity and shallow approach angles (<145°) lead to regimes of hyper-sensitivity and "terrain capture." These findings establish a unified quantitative framework for understanding track bifurcation and looping, offering crucial insights for assessing forecast uncertainty in mountainous regions.

This research aims to develop an educational board game, “Sustainable Home: Energy Challenge,” based on Monopoly by integrating sustainable development goals and renewable energy to use ChatGPT in human–computer collaboration. ChatGPT was used for game conceptualization, rule development, board creation, card design, and simulation in an iterative design. The developed board game demonstrated ChatGPT’s efficiency in educational game design and the benefits of human–computer collaboration. Game simulations validated the board game’s potential as a simulation tool to enhance diversity, cooperation, and strategic depth. The game effectively promoted SDG engagement and sustainable development education in gamified learning.

This study presents an innovative, dynamic model for predicting typhoon track deflections over complex terrain. Based on potential vorticity conservation, the model incorporates a topographic adjusting parameter (α) and a meridional adjusting velocity (MAV) to capture the vortex’s response to terrain variations. Simulations using an idealized bell-shaped mountain and Taiwan’s realistic topography reveal that steeper terrain gradients consistently deflect typhoon tracks southward. This steering effect intensifies with increasing vortex strength due to a larger α, leading to enhanced MAV. Shallower approach angles also amplify deflections due to prolonged terrain interaction. Results highlight the significant role of Taiwan’s Central Mountain Range in shaping typhoon trajectories. This model offers a refined approach for predicting typhoon behavior near complex terrain, advancing forecasting capabilities, and enhancing disaster preparedness strategies.

This study presents an innovative, dynamic model for predicting typhoon track deflections over complex terrain. Based on potential vorticity conservation, the model incorporates a topographic adjusting parameter (α) and a meridional adjusting velocity (MAV) to capture the vortex’s response to terrain variations. Simulations using an idealized bell-shaped mountain and Taiwan's realistic topography reveal that steeper terrain gradients consistently deflect typhoon tracks southward. This steering effect intensifies with increasing vortex strength due to a larger α, leading to enhanced MAV. Shallower approach angles also amplify deflections due to prolonged terrain interaction. Results highlight the significant role of Taiwan's Central Mountain Range in shaping typhoon trajectories. This model offers a refined approach for predicting typhoon behavior near complex terrain, advancing forecasting capabilities, and enhancing disaster preparedness strategies.

This study explores the implementation of an interdisciplinary curriculum in product and media design education and its impact on knowledge innovation and competency development. The curriculum is based on scaffolding theory, incorporating design proposals, workshops, digital design, marketing tests, and marketing activities guided by teachers and mentors from a branded ceramic workshop. The research findings demonstrate that the interdisciplinary curriculum facilitates knowledge innovation and fosters the development of students’ professional skills, creativity, and problem-solving skills. The study also highlights the importance of stable scaffolding, including artefact-, peer-, and teacher support, which significantly contributes to cultivating transformational competencies, as outlined in the 2030 OECD Learning Compass. Additionally, the collaboration with Shanshing Four Seasons Celadon Studio on a patented ceramic product, “Funny Monkey”, is a tangible example of the journey towards a triple-helix knowledge economy. This research underscores the importance of interdisciplinary curricula in promoting knowledge innovation and integrating transformational competencies in education. Scaffolding theory provides practical guidance for student learning and teaching strategies, presenting a sustainable roadmap for developing interdisciplinary curricula and offering a concrete and transferable pedagogical prototype for educational innovation.